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New England Section of the American Urological Association

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Using microRNA Expression from Biopsy Samples in Upper Tract Urothelial Carcinoma as a Predictive Model for Tumor Grade, Invasion and Survival
Aaron Berkenwald, MD1, Eric Katz, MD1, Brendan Browne, MD1, Chintan K. Patel, MD1, Travis Sullivan, PhD1, Eric J. Burks, MD2, Jay D. Raman, MD3, Joshua Warrick, MD3, David Canes, MD1, Kimberly M. Rieger-Christ, PhD1
1Lahey, Burlington, MA, 2Boston University, Boston, MA, 3Penn State, Hershey, PA

Introduction
Radical Nephroureterectomy (RNU) is the gold standard treatment for Upper Tract Urothelial Carcinoma (UTUC). However, less invasive treatment modalities exist for low grade (LG), non-invasive tumors. Determination of tumor characteristics are currently based on endoscopic biopsies, which often result in insufficient tissue for accurate diagnosis. Molecular analysis of UTUC biopsies may enable practitioners to make more informed clinical decisions and avoid overtreating less aggressive tumors. We propose that analyzing microRNA (miRNA) expression patterns from UTUC biopsies to predict final pathology on RNU samples may provide a framework for more effective diagnosis, and help predict survival.
Methods
Under an IRB-approved, study, total RNA was extracted from formalin-fixed, paraffin-embedded UTUC biopsy samples from 64 patients who subsequently underwent RNU from 2005-2018 at three high-volume institutions. Twenty screening samples were profiled via miRNA RT-qPCR array for 752 unique miRNAs. Differentially expressed miRNAs were then validation using 71 additional UTUC biopsy samples. In total, 39 high grade (HG) and 32 LG samples were analyzed using ROC curves and logistic regression to establish a predictive miRNA model corresponding to final pathological grade and invasion after RNU. Kaplan-Meier survival analysis was performed comparing statistically significant miRNA to pathologic grade and invasion from both biopsy and RNU samples.
Results
Screening array analysis identified 26 miRNAs differentially expressed between LG and HG tumors (p<0.05 and FDR<0.1). Of these, four were up-regulated and 22 were down-regulated in the HG, invasive tumors. Hierarchical clustering analysis yielded two distinct groups with miRNA expression patterns corresponding to final RNU pathology (p=0.029). Validation of these miRNA revealed correlation of miR-146b and 223-3p expression with invasive (p<0.05) and HG tumors (p<0.001). Predictive modeling of RNU invasion using miR-21-5p and 29c-3p in combination yielded sensitivity and specificity of 45.2% and 87.5% with a 0.74 AUC, compared to prediction from biopsy invasion sensitivity 32.1% and specificity 97.3% with AUC 0.65.
Survival analysis for miR-146b (HR 3.77, p=0.002) and 223-3p (HR 6.16, p<0.001) were compared to biopsy invasion (HR 2.97, p=0.032) and biopsy HG (HR 1.18, p=0.721). In combination, miR-146b and miR223-3p were associated with median survival of 13 months (p<0.001) compared to 54 months for biopsy invasion (p=0.006) and 87 months for biopsy HG (p=0.017).
Conclusions
We present distinct miRNA expression profiles of UTUC biopsies that show a statistically significant correlation with RNU tumor invasion and grade. We further suggest the ability of these miRNA to predict final pathologic stage. Finally, we highlight a statistically significant correlation between specific miRNA expression and poor overall survival.


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